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81
PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction ...
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82
Natural language processing as a tool to identify the Reddit particularities of cancer survivors around the time of diagnosis and remission: A pilot study ...
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83
Does Social Pressure Drive Persuasion in Online Fora? ...
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84
A Large-Scale Dataset for Empathetic Response Generation ...
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85
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews ...
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86
Sample Selection Guided by Domain and Task for Cross-Domain Targeted Sentiment Analysis ...
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87
Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training ...
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88
Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis ...
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89
Dimensional Emotion Detection from Categorical Emotion ...
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90
Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment Analysis with Affective Knowledge ...
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91
Unimodal and Crossmodal Refinement Network for Multimodal Sequence Fusion ...
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92
Reinforced Counterfactual Data Augmentation for Dual Sentiment Classification ...
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93
Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model ...
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94
Adverse Drug Reaction Classification of Tweets with Fusion of Text and Drug Representations ...
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95
Visually Grounded Reasoning across Languages and Cultures ...
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96
Multilingual and Multilabel Emotion Recognition using Virtual Adversarial Training ...
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97
Monolingual Pre-Trained Language Models for Tigrinya ...
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98
Implicit Sentiment Analysis with Event-centered Text Representation ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.551/ Abstract: Implicit sentiment analysis, aiming at detecting the sentiment of a sentence without sentiment words, has become an attractive research topic in recent years. In this paper, we focus on event-centric implicit sentiment analysis that utilizes the sentiment-aware event contained in a sentence to infer its sentiment polarity. Most existing methods in implicit sentiment analysis simply view noun phrases or entities in text as events or indirectly model events with sophisticated models. Since events often trigger sentiments in sentences, we argue that this task would benefit from explicit modeling of events and event representation learning. To this end, we represent an event as the combination of its event type and the event triplet . Based on such event representation, we further propose a novel model with hierarchical tensor-based composition mechanism to detect sentiment in text. In addition, we ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Sentiment Analysis
URL: https://dx.doi.org/10.48448/0mda-s882
https://underline.io/lecture/38062-implicit-sentiment-analysis-with-event-centered-text-representation
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99
Stock Market Tweets Data ...
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100
Affect Dynamic Signatures of Psychosis Risk ...
Li, Lilian. - : Open Science Framework, 2021
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